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google-ai-history-mcp

google-ai-history-mcp

by travispflanz

Import Google Ai Takeout Or Files

import_google_ai_takeout_or_files

Imports Google AI chats from Takeout, AI Studio Drive folders, NotebookLM, or JSON/MD files into local history for indexing and search.

Instructions

Import Google AI chats from Takeout, AI Studio Drive folder, NotebookLM, or JSON/MD.

Input Schema

NameRequiredDescriptionDefault
pathYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: not whether the import writes into a local store, whether existing chats are deduplicated or overwritten, whether re-running is safe, or whether it requires authentication. For a data-ingesting mutation tool, this is a substantial gap, with only the source enumeration adding any context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler and the source list placed immediately after the verb. It is efficiently sized, though its terseness is part of why behavioral and parameter detail is missing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, but for a one-parameter ingest tool with zero annotation coverage the description leaves the write behavior, path expectations, and re-import semantics undefined. An agent could not confidently predict the effect of calling it beyond 'something gets imported.'

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% for the single 'path' parameter, so the description must compensate. The source enumeration partially does so by indicating that the path may point at a Takeout archive, a Drive folder, or JSON/MD files, but it never says whether a file or directory is expected, which formats/extensions are valid, or whether paths are absolute or relative.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Specific verb ('Import') plus resource ('Google AI chats') and an enumerated set of accepted sources (Takeout, AI Studio Drive folder, NotebookLM, JSON/MD). This implicitly separates it from the sibling sync_google_ai_chats_from_browser, but it never names that sibling or states the distinction explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Listing the supported source types implies the situation in which to use it (you already have an export/archive), which is more than nothing. However, there is no explicit guidance on when to prefer this over sync_google_ai_chats_from_browser, no prerequisites, and no exclusions or re-import caveats.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.